Array (Dec 2021)
Hybrid optimization algorithm based optimal resource allocation for cooperative cognitive radio network
Abstract
Resource allocation plays a key role in cooperative cognitive radio networks (CCRNs), which is influenced by channel capacity, user density, transmission capacity, and user mobility. Many researchers worked on problem-solving in CCRN but did not solve navigation issues. User traffic affects the availability of the spectrum and creates complexity for the entire network. Next, keep in mind that the Multiple Matrix incorporates the dynamics of the multi-dolphin echolocation algorithm (MDEA), it calculates the best processing request among several requests from secondary users, and also takes cognitive radio users (CRUs). Thus, navigation has mobility enhanced gravitational search algorithm (MGSA) to expand navigation, thus increasing resource allocation productivity. The results of the modeling show that users have the necessary resources to ensure energy efficiency, productivity, and longevity under the proposed multi-objective resource allocation (MORA) scheme on mobility issues.
